Pandas filter after aggregation
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Is is possible to filter the data after groupby aggregation ?
I have aggregated the sum after applying groupby function, and want to see the rows where the sum is between some values.
Here is a basic code
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4]
], columns=['id', 'val'])
display(A)
display(A.groupby(['id']).agg({'val': ['sum', 'count']}))
I want count of val between 1 and 4 after aggregation
pandas pandas-groupby
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
add a comment |
0
Is is possible to filter the data after groupby aggregation ?
I have aggregated the sum after applying groupby function, and want to see the rows where the sum is between some values.
Here is a basic code
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4]
], columns=['id', 'val'])
display(A)
display(A.groupby(['id']).agg({'val': ['sum', 'count']}))
I want count of val between 1 and 4 after aggregation
pandas pandas-groupby
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35
add a comment |
0
0
0
Is is possible to filter the data after groupby aggregation ?
I have aggregated the sum after applying groupby function, and want to see the rows where the sum is between some values.
Here is a basic code
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4]
], columns=['id', 'val'])
display(A)
display(A.groupby(['id']).agg({'val': ['sum', 'count']}))
I want count of val between 1 and 4 after aggregation
pandas pandas-groupby
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
Is is possible to filter the data after groupby aggregation ?
I have aggregated the sum after applying groupby function, and want to see the rows where the sum is between some values.
Here is a basic code
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4]
], columns=['id', 'val'])
display(A)
display(A.groupby(['id']).agg({'val': ['sum', 'count']}))
I want count of val between 1 and 4 after aggregation
pandas pandas-groupby
pandas pandas-groupby
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
edited Nov 17 '18 at 12:57
Anupam Ghosh
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
asked Nov 17 '18 at 7:29
Anupam GhoshAnupam Ghosh
14217
14217
Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35
add a comment |
Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35
Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35
Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35
add a comment |
1 Answer
1
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oldest
votes
1
I dint understand if you wanted the sum between 1 and 4 or the count. So here is how i made it for the two options:
import pandas as pd
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4],
[1,2],
[1,2],
[1,2],
[1,2],
[1,2],
], columns=['id', 'val'])
s = A.groupby(['id']).agg({'val': ['sum', 'count']})
# If you want the count
s[(s['val']['count']<=4) & (s['val']['count']>=1)]
# If you want the sum
s[(s['val']['sum']<=4) & (s['sum']['count']>=1)]
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
I dint understand if you wanted the sum between 1 and 4 or the count. So here is how i made it for the two options:
import pandas as pd
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4],
[1,2],
[1,2],
[1,2],
[1,2],
[1,2],
], columns=['id', 'val'])
s = A.groupby(['id']).agg({'val': ['sum', 'count']})
# If you want the count
s[(s['val']['count']<=4) & (s['val']['count']>=1)]
# If you want the sum
s[(s['val']['sum']<=4) & (s['sum']['count']>=1)]
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
add a comment |
1
I dint understand if you wanted the sum between 1 and 4 or the count. So here is how i made it for the two options:
import pandas as pd
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4],
[1,2],
[1,2],
[1,2],
[1,2],
[1,2],
], columns=['id', 'val'])
s = A.groupby(['id']).agg({'val': ['sum', 'count']})
# If you want the count
s[(s['val']['count']<=4) & (s['val']['count']>=1)]
# If you want the sum
s[(s['val']['sum']<=4) & (s['sum']['count']>=1)]
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
add a comment |
1
1
1
I dint understand if you wanted the sum between 1 and 4 or the count. So here is how i made it for the two options:
import pandas as pd
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4],
[1,2],
[1,2],
[1,2],
[1,2],
[1,2],
], columns=['id', 'val'])
s = A.groupby(['id']).agg({'val': ['sum', 'count']})
# If you want the count
s[(s['val']['count']<=4) & (s['val']['count']>=1)]
# If you want the sum
s[(s['val']['sum']<=4) & (s['sum']['count']>=1)]
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
I dint understand if you wanted the sum between 1 and 4 or the count. So here is how i made it for the two options:
import pandas as pd
A = pd.DataFrame([
[1, 2],
[2, 3],
[1, 6],
[2, 7],
[3, 5],
[2, 9],
[4, 7],
[3, 5],
[3, 9],
[3, 4],
[1,2],
[1,2],
[1,2],
[1,2],
[1,2],
], columns=['id', 'val'])
s = A.groupby(['id']).agg({'val': ['sum', 'count']})
# If you want the count
s[(s['val']['count']<=4) & (s['val']['count']>=1)]
# If you want the sum
s[(s['val']['sum']<=4) & (s['sum']['count']>=1)]
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
answered Nov 17 '18 at 13:41
ManriqueManrique
599418
599418
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
add a comment |
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
I wanted the count :). Thanks for the answer
– Anupam Ghosh
Nov 17 '18 at 13:58
add a comment |
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Yes it is possible. Please share a minimal reproducible example so we can help you stackoverflow.com/help/mcve
– MedAli
Nov 17 '18 at 7:35